A computer program package for relative survival analysis

A computer program package has been constructed for use in patient survival analyses for chronic diseases based on aggregated data. The central concept of the analyses--the relative survival rate--is the ratio of the observed survival rate of the patients to the survival rate expected in a group in the general population similar to the group of patients at the beginning of the follow-up (interval), with respect to age, sex and calendar time. This quantity is used to measure patient survival adjusted for the effect of mortality attributable to the competing risks of death without employing information on causes of death of individual patients. The package contains three alternative methods of estimating the relative survival rates, two different ways of estimating the expectation of life for the patients, and five methods of testing the relative survival patterns using information on the whole follow-up period. Conventional survival and competing risk analysis can also be performed with the package. It is hoped that the package will facilitate standardization of statistical methodology and terminology in long-term survival studies for chronic diseases.     

Identifying 3D maximal common substructures using transputer networks

This paper describes the use of a multiprocessor system for identifying the maximal common substructure (MCS) between pairs of three-dimensional (3D) chemical structures. The system is constructed from Transputers, 32-bit RISC microprocessors produced by Inmos Ltd., linked together in a tree network. The MCS algorithm used, developed by Crandell and Smith, identifies the MCS by a breadth-first search in which individual atoms common to the structures are extended one atom at a time until no further extension of the common substructure can be obtained. Experiments using a Pascal-based simulation package demonstrate the feasibility of using a multiprocessor system to increase the speed of MCS identification. Experiments with networks of Transputers demonstrate that substantial increases in speed can be achieved in practice if, and only if, the MCS is large.     

Dynamic simulation of the human red blood cell metabolic network

We have developed a Mathematica application package to perform dynamic simulations of the red blood cell (RBC) metabolic network. The package relies on, and integrates, many years of mathematical modeling and biochemical work on red blood cell metabolism. The extensive data regarding the red blood cell metabolic network and the previous kinetic analysis of all the individual components makes the human RBC an ideal 'model' system for mathematical metabolic models. The Mathematica package can be used to understand the dynamics and regulatory characteristics of the red blood cell.     

multimark: an R package for analysis of capture–recapture data consisting of multiple “noninvasive” marks

I describe an open‐source R package, multimark , for estimation of survival and abundance from capture–mark–recapture data consisting of multiple “noninvasive” marks. Noninvasive marks include natural pelt or skin patterns, scars, and genetic markers that enable individual identification in lieu of physical capture. multimark provides a means for combining and jointly analyzing encounter histories from multiple noninvasive sources that otherwise cannot be reliably matched (e.g., left‐ and right‐sided photographs of bilaterally asymmetrical individuals). The package is currently capable of fitting open population Cormack–Jolly–Seber (CJS) and closed population abundance models with up to two mark types using Bayesian Markov chain Monte Carlo (MCMC) methods. multimark can also be used for Bayesian analyses of conventional capture–recapture data consisting of a single‐mark type. Some package features include (1) general model specification using formulas already familiar to most R users, (2) ability to include temporal, behavioral, age, cohort, and individual heterogeneity effects in detection and survival probabilities, (3) improved MCMC algorithm that is computationally faster and more efficient than previously proposed methods, (4) Bayesian multimodel inference using reversible jump MCMC, and (5) data simulation capabilities for power analyses and assessing model performance. I demonstrate use of multimark using left‐ and right‐sided encounter histories for bobcats (Lynx rufus) collected from remote single‐camera stations in southern California. In this example, there is evidence of a behavioral effect (i.e., trap “happy” response) that is otherwise indiscernible using conventional single‐sided analyses. The package will be most useful to ecologists seeking stronger inferences by combining different sources of mark–recapture data that are difficult (or impossible) to reliably reconcile, particularly with the sparse datasets typical of rare or elusive species for which noninvasive sampling techniques are most commonly employed. Addressing deficiencies in currently available software, multimark also provides a user‐friendly interface for performing Bayesian multimodel inference using capture–recapture data consisting of a single conventional mark or multiple noninvasive marks.     

FLOSS: flexible ordered subset analysis for linkage mapping of complex traits

The FLOSS software package is a flexible framework for ordered subset analysis. FLOSS is specifically designed for use with the Merlin linkage analysis package, but FLOSS can be used with any linkage analysis software package that reports NPL Z-scores for each locus and family. When FLOSS is used with the Merlin linkage analysis package, one can use either non-parametric Z-scores or Kong and Cox linear allele sharing model LOD scores. Monte Carlo P-values are calculated using a permutation test with an efficient Besag-Clifford sequential stopping rule. FLOSS also has a flexible tool for assigning family covariate scores from Merlin input files. FLOSS includes user documentation and is written in Java for easy portability. The FLOSS source code is documented and designed to be extensible.     

glmm.hp: an R package for computing individual effect of predictors in generalized linear mixed models

glmm.hp:一个计算广义线性混合模型中单个预测变量效应的R包 广义线性混合效应模型(GLMMs)是当代生态学研究中广泛应用的数据分析模型。然而,确定GLMMs中共线性的预测变量(固定效应)对响应变量的相对重要性是个挑战。基于适用于多元分析的‘平均共享方差’的算法,我们开发一个新的R包glmm.hp来分解GLMMs中由固定效应解释的边际(marginal)R²。我们论述了该软件包的工作原理并通过模拟数据集演示了该软件包的使用。glmm.hp 包的输出结果为每个预测变量将获得一个独自的(individual)边际R²,且它们的总和刚好等于模型总的边际R²。总之,我们相信glmm.hp包将有助于解释GLMMs 的输出结果。     

Automatic updating of the EMBL database via EMBNet

The paper describes a procedure for updating the EMBL (EuropeanMolecular Biology Laboratory, Heidelberg) database of nucleicacid sequences and its indexes used by the University of WisconsinGenetics Computer Group (GCG) software package, using updatedentries for this database distributed via EMBNet. At presentthe procedure is being run on a MRC Clinical Research Centre's(CRC) SUN 4/280 server using SUNOS version 4.0.1 operating system.     

sars: an R package for fitting,evaluating and comparing species–area relationship models

The species–area relationship (SAR) constitutes one of the most general ecological patterns globally. A number of different SAR models have been proposed. Recent work has shown that no single model universally provides the best fit to empirical SAR datasets: multiple models may be of practical and theoretical interest. However, there are no software packages available that a) allow users to fit the full range of published SAR models, or b) provide functions to undertake a range of additional SAR‐related analyses. To address these needs, we have developed the R package ‘sars’ that provides a wide variety of SAR‐related functionality. The package provides functions to: a) fit 20 SAR models using non‐linear and linear regression, b) calculate multi‐model averaged curves using various information criteria, and c) generate confidence intervals using bootstrapping. Plotting functions allow users to depict and scrutinize the fits of individual models and multi‐model averaged curves. The package also provides additional SAR functionality, including functions to fit, plot and evaluate the random placement model using a species–sites abundance matrix, and to fit the general dynamic model of oceanic island biogeography. The ‘sars’ R package will aid future SAR research by providing a comprehensive set of simple to use tools that enable in‐depth exploration of SARs and SAR‐related patterns. The package has been designed to allow other researchers to add new functions and models in the future and thus the package represents a resource for future SAR work that can be built on and expanded by workers in the field.     

xRing—An R package to identify and measure tree-ring features using X-ray microdensity profiles

Climate influences tree-ring density and ring-density variables extracted from X-ray images have been widely used for climate reconstructions. The R package xRing was developed to identify and measure tree rings on X-ray microdensity profiles automatically. This package is available for free and it offers functions to visualize and calibrate X-ray images, to detect tree-ring borders and to identify earlywood-latewood transition using wood density variations at the inter- and the intra-ring scale. The most important functions are calibrateFilm, detectRings, correctRings, detectEwLw, and getDensity. Outputs of these functions are S3 objects, for which specific methods are provided, including plot and print. The non-linear relationship between optical density of the film and wood density is defined by the function calibrateFilm. The function detectRings detects tree rings using wood density profiles as input. This function uses the difference between local maximum and minimum values to identify tree-ring borders automatically. The correctRings function is used to call a Graphical User Interface (GUI) to visualize and to correct tree-ring borders manually. After correcting tree-ring borders, the detectEwLw function is used to compute earlywood and latewood widths by dividing rings according to relative intra-ring density changes. The getDensity function computes for each tree ring the minimum (maximum) density and the mean earlywood, latewood and whole-ring density. Finally, a list with dataframes with tree-ring width and density variables can be obtained using the function getRwls. One of the major advantages of xRing package is that requires little knowledge of R language, but at the same time it can be easily changed or adapted by experienced users.     

Necks and networks: a preliminary study of population structure in the reticulated giraffe (Giraffa camelopardalis reticulata de Winston)

This paper describes a method of scoring the neck pattern of reticulated giraffes as a simple code that can be searched for in an Excel spreadsheet. This enables several hundred individual giraffe to be recognized and repeatedly found within a database. Possible sources of error are described and quantified. Data on group size, dispersal within groups and social network patterns are described. The latter is facilitated using Ucinet 6.85 for Windows, a software package that helps to visualize and analyse such networks.     

Computer-Aided Prediction of Long-Term Prognosis of Patients with Ulcerative Colitis after Cytoapheresis Therapy

Cytoapheresis (CAP) therapy is widely used in ulcerative colitis (UC) patients with moderate to severe activity in Japan. The aim of this study is to predict the need of operation after CAP therapy of UC patients on an individual level using an artificial neural network system (ANN). Ninety UC patients with moderate to severe activity were treated with CAP. Data on the patients’ demographics, medication, clinical activity index (CAI) and efficacy of CAP were collected. Clinical data were divided into training data group and validation data group and analyzed using ANN to predict individual outcomes. The sensitivity and specificity of predictive expression by ANN were 0.96 and 0.97, respectively. Events of admission, operation, and use of immunomodulator, and efficacy of CAP were significantly correlated to the outcome. Requirement of operation after CAP therapy was successfully predicted by using ANN. This newly established ANN strategy would be used as powerful support of physicians in the clinical practice.     

PGAAS: a prokaryotic genome assembly assistant system

MOTIVATION: In order to accelerate the finishing phase of genome assembly, especially for the whole genome shotgun approach of prokaryotic species, we have developed a software package designated prokaryotic genome assembly assistant system (PGAAS). The approach upon which PGAAS is based is to confirm the order of contigs and fill gaps between contigs through peptide links obtained by searching each contig end with BLASTX against protein databases. RESULTS: We used the contig dataset of the cyanobacterium Synechococcus sp. strain PCC7002 (PCC7002), which was sequenced with six-fold coverage and assembled using the Phrap package. The subject database is the protein database of the cyanobacterium, Synechocystis sp. strain PCC6803 (PCC6803). We found more than 100 non-redundant peptide segments which can link at least 2 contigs. We tested one pair of linked contigs by sequencing and obtained satisfactory result. PGAAS provides a graphic user interface to show the bridge peptides and pier contigs. We integrated Primer3 into our package to design PCR primers at the adjacent ends of the pier contigs. AVAILABILITY: We tested PGAAS on a Linux (Redhat 6.2) PC machine. It is developed with free software (MySQL, PHP and Apache). The whole package is distributed freely and can be downloaded as UNIX compress file: ftp://ftp.cbi.pku.edu.cn/pub/software/unix/pgaas1.0.tar.gz. The package is being continually updated.     

affy--analysis of Affymetrix GeneChip data at the probe level

MOTIVATION: The processing of the Affymetrix GeneChip data has been a recent focus for data analysts. Alternatives to the original procedure have been proposed and some of these new methods are widely used. RESULTS: The affy package is an R package of functions and classes for the analysis of oligonucleotide arrays manufactured by Affymetrix. The package is currently in its second release, affy provides the user with extreme flexibility when carrying out an analysis and make it possible to access and manipulate probe intensity data. In this paper, we present the main classes and functions in the package and demonstrate how they can be used to process probe-level data. We also demonstrate the importance of probe-level analysis when using the Affymetrix GeneChip platform.     

A fast and efficient method for screening of nested deletions using PCR

Summary A procedure is presented for using PCR to screen individual colonies, representing clones obtained after controlled unidirectional exonuclease III digestion, for the sizes of the individual inserts. Many clones can be screened at one time since the plasmid templates used for amplification need not be purified but are prepared from individual colonies by a simple procedure that takes less than 30 minutes.     

PRIMEGENS: robust and efficient design of gene-specific probes for microarray analysis

MOTIVATION: DNA microarray is a powerful high-throughput tool for studying gene function and regulatory networks. Due to the problem of potential cross hybridization, using full-length genes for microarray construction is not appropriate in some situations. A bioinformatic tool, PRIMEGENS, has recently been developed for the automatic design of PCR primers using DNA fragments that are specific to individual open reading frames (ORFs). RESULTS: PRIMEGENS first carries out a BLAST search for each target ORF against all other ORFs of the genome to quickly identify possible homologous sequences. Then it performs optimal sequence alignment between the target ORF and each of its homologous ORFs using dynamic programming. PRIMEGENS uses the sequence alignments to select gene- specific fragments, and then feeds the fragments to the Primer3 program to design primer pairs for PCR amplification. PRIMEGENS can be run from the command line on Unix/Linux platforms as a stand-alone package or it can be used from a Web interface. The program runs efficiently, and it takes a few seconds per sequence on a typical workstation. PCR primers specific to individual ORFs from Shewanella oneidensis MR-1 and Deinococcus radiodurans R1 have been designed. The PCR amplification results indicate that this method is very efficient and reliable for designing specific probes for microarray analysis.     

COPASutils: An R Package for Reading,Processing, and Visualizing Data from COPAS Large-Particle Flow Cytometers

The R package COPASutils provides a logical workflow for the reading, processing, and visualization of data obtained from the Union Biometrica Complex Object Parametric Analyzer and Sorter (COPAS) or the BioSorter large-particle flow cytometers. Data obtained from these powerful experimental platforms can be unwieldy, leading to difficulties in the ability to process and visualize the data using existing tools. Researchers studying small organisms, such as Caenorhabditis elegans, Anopheles gambiae, and Danio rerio, and using these devices will benefit from this streamlined and extensible R package. COPASutils offers a powerful suite of functions for the rapid processing and analysis of large high-throughput screening data sets.     

Using plusTipTracker Software to Measure Microtubule Dynamics in Xenopus laevis Growth Cones

Microtubule (MT) plus-end-tracking proteins (+TIPs) localize to the growing plus-ends of MTs and regulate MT dynamics^1,2. One of the most well-known and widely-utilized +TIPs for analyzing MT dynamics is the End-Binding protein, EB1, which binds all growing MT plus-ends, and thus, is a marker for MT polymerization¹. Many studies of EB1 behavior within growth cones have used time-consuming and biased computer-assisted, hand-tracking methods to analyze individual MTs^1-3. Our approach is to quantify global parameters of MT dynamics using the software package, plusTipTracker⁴, following the acquisition of high-resolution, live images of tagged EB1 in cultured embryonic growth cones⁵. This software is a MATLAB-based, open-source, user-friendly package that combines automated detection, tracking, visualization, and analysis for movies of fluorescently-labeled +TIPs. Here, we present the protocol for using plusTipTracker for the analysis of fluorescently-labeled +TIP comets in cultured Xenopus laevis growth cones. However, this software can also be used to characterize MT dynamics in various cell types^6-8.     

Apple Macintosh programs for nucleic and protein sequence analyses

This paper describes a package of programs for handling and analyzing nucleic acid and protein sequences using the Apple Macintosh microcomputer. There are three important features of these programs: first, because of the now classical Macintosh interface the programs can be easily used by persons with little or no computer experience. Second, it is possible to save all the data, written in an editable scrolling text window or drawn in a graphic window, as files that can be directly used either as word processing documents or as picture documents. Third, sequences can be easily exchanged with any other computer. The package is composed of thirteen programs, written in Pascal programming language.